12 May, 2020

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Introduction

Data set:

  • breast cancer

  • proteomics by mass spectrometry

  • four cancer classes:

 

Goal:

  • Explore the data to identify patterns

  • Create models to predict breast cancer class  

Project’s GitHub repository

Material and Methods

Material and Methods

Material and Methods

Material and Methods

Material and Methods

Course-related packages

  • tidyverse
  • broom
  • patchwork
  • keras/tensorflow

Course-unrelated packages

  • gridExtra
  • RColorBrewer

Results — no outliers on total protein expression

Results — breast cancer classes in the dataset are well represented

Results — breast cancer classes do not discriminate on age

Results — breast cancer and gender

Results — protein expresion heatmap

Results — dimentionality reduction

Results — K-means clustering

Results — ANN model’s structure

Results — ANN performance

Discussion

  • What could have been better

  • maybe we can say it is good to merge both omics data and clinical metadata

  • further work

The end